A Short Review on Cryoprotectants for 3D Protein Structure Analysis

Freeze-drying revolution: unleashing the potential of lyophilization in advancing drug delivery systems

Lyophilization also known as freeze-drying is a technique that has been employed to enhance the long-term durability of nanoparticles (NPs) that are utilized for drug delivery applications. This method is used to prevent their instability in suspension. However, this dehydration process can cause stress to the NPs, which can be alleviated by the incorporation of excipients like cryoprotectants and lyoprotectants. Nevertheless, the freeze-drying of NPs is often based on empirical principles without considering the physical-chemical properties of the formulations and the engineering principles of freeze-drying. For this reason, it is crucial to optimize the formulations and the freeze-drying cycle to obtain a good lyophilizate and ensure the preservation of NPs stability. Moreover, proper characterization of the lyophilizate and NPs is of utmost importance in achieving these goals. This review aims to update the recent advancements, including innovative formulations and novel approaches, contributing to the progress in this field, to obtain the maximum stability of formulations. Additionally, we critically analyze the limitations of lyophilization and discuss potential future directions. It addresses the challenges faced by researchers and suggests avenues for further research to overcome these limitations. In conclusion, this review is a valuable contribution to the understanding of the parameters involved in the freeze-drying of NPs. It will definitely aid future studies in obtaining lyophilized NPs with good quality and enhanced drug delivery and therapeutic benefits.

PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank

While the Protein Data Bank (PDB) contains a wealth of structural information on ligands bound to macromolecules, their analysis can be challenging due to the large amount and diversity of data. Here, we present PDBe CCDUtils, a versatile toolkit for processing and analysing small molecules from the PDB in PDBx/mmCIF format. PDBe CCDUtils provides streamlined access to all the metadata for small molecules in the PDB and offers a set of convenient methods to compute various properties using RDKit, such as 2D depictions, 3D conformers, physicochemical properties, scaffolds, common fragments, and cross-references to small molecule databases using UniChem. The toolkit also provides methods for identifying all the covalently attached chemical components in a macromolecular structure and calculating similarity among small molecules. By providing a broad range of functionality, PDBe CCDUtils caters to the needs of researchers in cheminformatics, structural biology, bioinformatics and computational chemistry.

GCmapCrys: Integrating graph attention network with predicted contact map for multi-stage protein crystallization propensity prediction

X-ray crystallography is the major approach for atomic-level protein structure determination. Since not all proteins can be easily crystallized, accurate prediction of protein crystallization propensity is critical to guiding the experimental design and improving the success rate of X-ray crystallography experiments. In this work, we proposed a new deep learning pipeline, GCmapCrys, for multi-stage crystallization propensity prediction through integrating graph attention network with predicted protein contact map. Experimental results on 1548 proteins with known crystallization records demonstrated that GCmapCrys increased the value of Matthew's correlation coefficient by 37.0% in average compared to state-of-the-art protein crystallization propensity predictors. Detailed analyses show that the major advantages of GCmapCrys lie in the efficiency of the graph attention network with predicted contact map, which effectively associates the residue-interaction knowledge with crystallization pattern. Meanwhile, the designed four sequence-based features can be complementary to further enhance crystallization propensity proprediction.

Protein Design Strategies for the Structural–Functional Studies of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are an important family of membrane proteins responsible for many physiological functions in human body. High resolution GPCR structures are required to understand their molecular mechanisms and perform rational drug design, as GPCRs play a crucial role in a variety of diseases. That is difficult to obtain for the wild-type proteins because of their low stability. In this review, we discuss how this problem can be solved by using protein design strategies developed to obtain homogeneous stabilized GPCR samples for crystallization and cryoelectron microscopy.